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An adaptive fuzzy technique for real-time detection of multiple faces against a complex background

by Dyut Kumar Sil, Subhadip Basu, Mita Nasipuri
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 1 - Number 23
Year of Publication: 2010
Authors: Dyut Kumar Sil, Subhadip Basu, Mita Nasipuri
10.5120/543-707

Dyut Kumar Sil, Subhadip Basu, Mita Nasipuri . An adaptive fuzzy technique for real-time detection of multiple faces against a complex background. International Journal of Computer Applications. 1, 23 ( February 2010), 19-24. DOI=10.5120/543-707

@article{ 10.5120/543-707,
author = { Dyut Kumar Sil, Subhadip Basu, Mita Nasipuri },
title = { An adaptive fuzzy technique for real-time detection of multiple faces against a complex background },
journal = { International Journal of Computer Applications },
issue_date = { February 2010 },
volume = { 1 },
number = { 23 },
month = { February },
year = { 2010 },
issn = { 0975-8887 },
pages = { 19-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume1/number23/543-707/ },
doi = { 10.5120/543-707 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:48:40.501240+05:30
%A Dyut Kumar Sil
%A Subhadip Basu
%A Mita Nasipuri
%T An adaptive fuzzy technique for real-time detection of multiple faces against a complex background
%J International Journal of Computer Applications
%@ 0975-8887
%V 1
%N 23
%P 19-24
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper describes a real-time face detection system which is capable of processing video frames extremely rapidly while achieving high detection rate. The primary contribution of this paper is development of a fast algorithm for partitioning each frame into sub-images, detection of potential facial sub-images and real-time clustering of such potential sub-images into isolated objects/faces. A set of experiments in the domain of real-time face detection are presented. The performance of the system is comparable to some well known previous systems [5, 6, 8, 9]. Being implemented on a conventional desktop, face detection could be done at the rate of 13 frames per second.

References
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  2. R. Féraud, O. J. Bernier, J. E. Viallet and M. Collobert, “A Fast and Accurate Face Detector Based on Neural Networks”, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 23, no.1, pp. 42-53, January-2001.
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  6. http://www.ces.clemson.edu/~stb/blepo
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  8. H. Rowley, s. Baluja and Kanade, T. 1998. “Neural network- based face detection”, IEEE Patt. Anal. Mach. Intell., 20:22- 38.
  9. H. Schneiderman and Kanade, T. 2000. “A statistical method for 3D object detection applied for faces and cars”, International Conference on Computer Vision.
Index Terms

Computer Science
Information Sciences

Keywords

Real-time clustering computer vision face detection

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